INVESTIGATING THE GROUNDWATER QUALITY IN AQUIFER OF GONABAD BASIN, KHORASAN RAZAVI, USING MULTIVARIATE STATISTICAL METHODS AND ARTIFICIAL INTELLIGENCE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ROOKI R.; ARYAFAR A.; ADELINASAB J.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF MINERAL RESOURCES ENGINEERING Year:2017 | Volume:2 | Issue:1 Page(s): 49-61

Download Full-Text

Persian Verion

View:

1,006

Download:

Cites:

Information Journal Paper

Title

INVESTIGATING THE GROUNDWATER QUALITY IN AQUIFER OF GONABAD BASIN, KHORASAN RAZAVI, USING MULTIVARIATE STATISTICAL METHODS AND ARTIFICIAL INTELLIGENCE

Author(s)

ROOKI R. | ARYAFAR A. | ADELINASAB J. | Issue Writer Certificate

Keywords

HYDROCHEMISTRY

R- MODE FACTOR ANALYSIS

ARTIFICIAL NEURAL NETWORK

GONABAD BASIN

Abstract

The study on the quality of groundwater is important for drinking, industry and agriculture purposes. In this research, the hydrochemical data collected from exploitation wells in GONABAD BASIN- Khorasan Razavi, have been studied in period of 5 years (from 85 to 90). Graphical methods and classification of underground water quality show that the type of water is mainly that of sodium sulfate. Spatial distribution of water quality using multivariate statistical R-mode model states that water quality in this basin is affected by two factors. The first factor which is known as salinity and water hardness in plain is the linear combination of Ca2+, Mg2+, Na+, SO42-, Cl-, TH and EC. The second factor is the combination of HCO3-, CO32- and pH which indicates water alkalinity for which higher pH is an evidence. Further in the research, the modeling of quality parameters TDS, EC and TH is done with chemical parameters such as primary ions and pH using ARTIFICIAL NEURAL NETWORK. The comparison of results obtained from filed with those of neural network is very analogous showing the high ability of this method for water quality prediction. Therefore, in case of lack of data in the area, this model can be used to predict water quality in target locations. The results can be used to environmental management and better exploitation of groundwater resources.

Cites

No record.

References

No record.

Cite

APA: Copy

ROOKI, R., ARYAFAR, A., & ADELINASAB, J.. (2017). INVESTIGATING THE GROUNDWATER QUALITY IN AQUIFER OF GONABAD BASIN, KHORASAN RAZAVI, USING MULTIVARIATE STATISTICAL METHODS AND ARTIFICIAL INTELLIGENCE. JOURNAL OF MINERAL RESOURCES ENGINEERING, 2(1 ), 49-61. SID. https://sid.ir/paper/265419/en

Vancouver: Copy

ROOKI R., ARYAFAR A., ADELINASAB J.. INVESTIGATING THE GROUNDWATER QUALITY IN AQUIFER OF GONABAD BASIN, KHORASAN RAZAVI, USING MULTIVARIATE STATISTICAL METHODS AND ARTIFICIAL INTELLIGENCE. JOURNAL OF MINERAL RESOURCES ENGINEERING[Internet]. 2017;2(1 ):49-61. Available from: https://sid.ir/paper/265419/en

IEEE: Copy

R. ROOKI, A. ARYAFAR, and J. ADELINASAB, “INVESTIGATING THE GROUNDWATER QUALITY IN AQUIFER OF GONABAD BASIN, KHORASAN RAZAVI, USING MULTIVARIATE STATISTICAL METHODS AND ARTIFICIAL INTELLIGENCE,” JOURNAL OF MINERAL RESOURCES ENGINEERING, vol. 2, no. 1 , pp. 49–61, 2017, [Online]. Available: https://sid.ir/paper/265419/en

Related Journal Papers